{"id":"W4406630040","doi":"10.1007/s10340-024-01865-z","title":"Efficacy of unbaited and baited green multi-funnel traps for detection of Agrilus species and other wood-boring beetle taxa","year":2025,"lang":"en","type":"article","venue":"Journal of Pest Science","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Food Inspection Agency; Canadian Forest Service","funders":"Canadian Forest Service; Natural Resources Canada; Animal and Plant Health Inspection Service; Università degli Studi di Padova; U.S. Forest Service; European Commission; U.S. Department of Agriculture; Department for Environment, Food and Rural Affairs, UK Government; Pennsylvania Department of Agriculture; Canadian Food Inspection Agency","keywords":"Biology; Agrilus; Buprestidae; Taxon; Entomology; Ecology; Funnel; Botany; Zoology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006525786,0.00006451499,0.0001435694,0.0001817083,0.0001263919,0.00001311716,0.0001839567,0.0000319056,0.00003079537],"category_scores_gemma":[0.0001670421,0.00005197867,0.00003422557,0.000465312,0.0007048214,0.0002128876,0.0000971583,0.00006672182,5.87183e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004937812,"about_ca_system_score_gemma":0.00001859133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001161042,"about_ca_topic_score_gemma":0.0003008156,"domain_scores_codex":[0.9992911,0.00001758646,0.0002576181,0.0001305678,0.0001692799,0.0001338004],"domain_scores_gemma":[0.9994884,0.00009536436,0.000257757,0.00007814768,0.00003216194,0.00004815539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001747788,0.0001985869,0.04180428,0.00008157345,0.00002825019,0.000002369494,0.0007882969,0.0008162843,0.9439722,0.0006616215,0.00006367805,0.01140813],"study_design_scores_gemma":[0.001030561,0.0002962047,0.9634594,0.00005286426,0.00003291954,0.00001101653,0.0002027828,0.001891269,0.03144327,0.0003070301,0.001215223,0.00005748117],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950501,0.00006333365,0.004084948,0.00008262089,0.0001530274,0.0001493964,0.000002828901,0.000002956075,0.0004107344],"genre_scores_gemma":[0.9974082,0.00002339567,0.002168505,0.00005037102,0.000012867,0.000001658512,5.6383e-8,0.000002456475,0.0003325616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9216551,"threshold_uncertainty_score":0.2596944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01404926375053076,"score_gpt":0.2509444451204296,"score_spread":0.2368951813698989,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}